Category: Space Science

Langmuir probes are instruments used to study space plasma. These instruments are immensely popular owing to the simplicity of their design and hence have a rich heritage of being flown on wide variety of space missions.

Langmuir Probes on-board the Rosetta : Comet Hunter (left) and on-board the International Space Station (right).

In simplest terms, these probes could be described as biased electrodes that current collect from the surrounding plasma. The theory of Langmuir probes involves interpreting these current measurements into useful physical quantities like density and temperature, which reveal the state of the space plasma. This theory has been developed and advanced for almost a century now, which has enabled these probes to be used in all kinds of plasma. However, these theories are based on the inherent assumption of the probe surface having uniform surface properties. Steps like using inert materials with uniform work function for probe construction, heating the probe through the course of the flight etc. have all been adapted to ensure this requirement.

However, there have been cases where the uniformity of the surface has been disturbed during construction, assembling, in-flight, rendering the measurements to be faulty. Steps to circumvent the change in surface behavior if the change is seen to be uniform across the surface (think of water vapor deposited uniformly across the entire probe surface), has been successfully implemented. But, the case when the change is nonuniform and hence the surface behavior is spatially patchy, has not been resolved so far. With the advent of smaller platform missions through CubeSats, resolving this problem is especially important since elaborate steps to satisfy the requirement of uniform surface properties are not always feasible owing to the cost and space constraints.

My research deals with how to combat this issue. We have developed a model that accounts for this patchy surface behavior through an ensemble of microscopic collectors and the surface variance of this ensemble has been modeled into the resulting current collection. This model has been developed from first principles making it adaptable to all space regimes and we have also constructed models for all probe geometries.

We used this model to study current from a sounding rocket mission called STORMS which had a spatially nonuniform probe surface despite the use of precautionary design measures. Below is a snapshot of the model vs rocket data that shows the success of the model in simulating the current collection under patchy surface conditions. To learn more about the development of the model and the rocket data shown above, head over here.

Here are the places where this work has been presented and reported so far:

P. Suresh and C.M. Swenson, Can we make reliable plasma measurements from Langmuir Probes on CubeSats?, Measurement Techniques in Solar & Space Physics, April 2015.

The terrestrial atmospheric region between the altitudes of 90 km and 600 km is known as the thermosphere. The thermosphere is continuously modulated by particle emissions and magnetic fields that originate from the sun. These fields and emissions are intensified during events known as geomagnetic storms which alter the state of the thermosphere by dumping gigawatts of energy.

Geomagnetic Storm (Credit: NASA Science)

This energy is mostly deposited in the lower thermospheric regions of 150 km and below and can have potential hazardous repercussions on the technological assets of mankind. These storms can disrupt radio communication systems, interrupt electric power systems, threaten the safety of astronauts, and disrupt global position systems (GPS), all of which can wreck havoc on the technology-dependent human society. Hence, it is essential that we understand and predict the influence of these storms on the terrestrial thermosphere.

Our current understanding of the thermospheric response to the geomagnetic storms energy is limited to the observations of the thermospheric state at orbital altitudes of 400 km and above. The state of the terrestrial thermosphere at altitudes of 150 km and below during geomagnetic storms is largely unknown. This lower thermospheric response is instrumental in understanding and predicting the thermospheric state during geomagnetic storms. My research bridges this gap in understanding of the thermospheric response to storms by observing the change in lower thermospheric state in the event of geomagnetic storm occurrences.

To understand the thermospheric state, I use temperature data from SABER instrument on-board the TIMED satellite. What’s cool about SABER data is that it gives us global measurements of the lower thermosphere and has been operational since 2002, enabling statistical studies. I construct data driven models from SABER to understand what factors influence the storm response, what are the spatial and temporal attributes of the storm response, and, how do the existing physics and empirical models fare when compared to our data-driven modeling.

One of the aspects of this work involves separating all non-storm trends and modulations from the data to isolate storm response alone. To do so, we have built a “quiet time variation model” of the thermosphere. Using this model, we have been able to isolate storm response and understand how the internal state of the thermosphere gets altered by the storm. Here is a snapshot of the results from our study which provide a first ever global lower thermosperic storm response.

My research also deals with understanding how do the different features of the sun and thermosphere control this interaction between the storm energy and the thermosphere. For instance, how does the phase of the solar cycle control the thermospheric response? , how does the duration of the storm influence the thermospheric behavior?. To study this, we use machine learning to construct predictive models of the storm response and look at the models to figure out the influence of the feature space ( solar cycle, storm strength, storm duration etc.) . Below is a decision tree from one of our studies that shows the influence of various storm predictors in describing the presence or absence of delay in thermospheric response to storm energy (The numbers in red are resubstitution errors.)

This work has able to answer several outstanding questions on lower thermospheric response, such as, the time taken by the storm energy to overcome the thermsopheric inertia, the expected temperature increase for different classes of storms, how long does it take for the atmosphere to recover following a storm. You can read more about our findings and the models here.